Artificial intelligence (AI) is the intelligence of machines and the branch of computer science that aims to create it. AI textbooks define the field as "the study and design of intelligent agents" where an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success. John McCarthy, who coined the term in 1955, defines it as "the science and engineering of making intelligent machines."

In 1956, Herb Simon... predicted that within ten years computers would beat the world chess champion, compose "aesthetically satisfying" original music, and prove new mathematical theorems. It took forty years, not ten, but all these goals were achieved—and within a few years of each other! The music composed by David Cope's programs cannot be distinguished... from that composed by Mozart, Beethoven, and Bach. In 1976, a computer was used in the proof of the long-unsolved "four color problem."

Michael J. Beeson, "The Mechanization of Mathematics," in Alan Turing: Life and Legacy of a Great Thinker (2004)

It may be that our role on this planet is not to worship God but to create him.

The question of whether a computer is playing chess, or doing long division, or translating Chinese, is like the question of whether robots can murder or airplanes can fly -- or people; after all, the "flight" of the Olympic long jump champion is only an order of magnitude short of that of the chicken champion (so I'm told). These are questions of decision, not fact; decision as to whether to adopt a certain metaphoric extension of common usage.

I have grown accustomed to the disrespect expressed by some of the participants for their colleagues in the other disciplines. "Why, Dan," ask the people in artificial intelligence, "do you waste your time conferring with those neuroscientists? They wave their hands about 'information processing' and worry about where it happens, and which neurotransmitters are involved, but they haven't a clue about the computational requirements of higher cognitive functions." "Why," ask the neuroscientists, "do you waste your time on the fantasies of artificial intelligence? They just invent whatever machinery they want, and say unpardonably ignorant things about the brain." The cognitive psychologists, meanwhile, are accused of concocting models with neither biological plausibility nor proven computational powers; the anthropologists wouldn't know a model if they saw one, and the philosophers, as we all know, just take in each other's laundry, warning about confusions they themselves have created, in an arena bereft of both data and empirically testable theories. With so many idiots working on the problem, no wonder consciousness is still a mystery. All these charges are true, and more besides, but I have yet to encounter any idiots. Mostly the theorists I have drawn from strike me as very smart people – even brilliant people, with the arrogance and impatience that often comes with brilliance – but with limited perspectives and agendas, trying to make progress on the hard problems by taking whatever shortcuts they can see, while deploring other people's shortcuts. No one can keep all the problems and details clear, including me, and everyone has to mumble, guess and handwave about large parts of the problem.

Recent researchers in artificial intelligence and computational methods use the term swarm intelligence to name collective and distributed techniques of problem solving without centralized control or provision of a global model. … the intelligence of the swarm is based fundamentally on communication. … the member of the multitude do not have to become the same or renounce their creativity in order to communicate and cooperate with each other. They remain different in terms of race, sex, sexuality and so forth. We need to understand, then, is the collective intelligence that can emerge from the communication and cooperation of such varied multiplicity.

The development of full artificial intelligence could spell the end of the human race. We cannot quite know what will happen if a machine exceeds our own intelligence, so we can't know if we'll be infinitely helped by it, or ignored by it and sidelined, or conceivably destroyed by it.

A computer program written by researchers at Argonne National Laboratory in Illinois has come up with a major mathematical proof that would have been called creative if a human had thought of it. In doing so, the computer has, for the first time, got a toehold into pure mathematics, a field described by its practitioners as more of an art form than a science. ...Dr. McCune's proof concerns a conjecture that is the very epitome of pure mathematics. ...His computer program proved that a set of three equations is equivalent to a Boolean algebra...

Gina Kolata, "With Major Math Proof, Brute Computers Show Flash of Reasoning Power" The New York Times (Dec 10, 1996)

Any aeai [A.I., artificial intelligence] smart enough to pass a Turing test is smart enough to know to fail it.

A century ago, we had essentially no way to start to explain how thinking works. Then psychologists like Sigmund Freud and Jean Piaget produced their theories about child development. Somewhat later, on the mechanical side, mathematicians like Kurt Gödel and Alan Turing began to reveal the hitherto unknown range of what machines could be made to do. These two streams of thought began to merge only in the 1940s, when Warren McCulloch and Walter Pitts began to show how machines might be made to see, reason, and remember. Research in the modern science of Artificial Intelligence started only in the 1950's, stimulated by the invention of modern computers. This inspired a flood of new ideas about how machines could do what only minds had done previously.

There is probably no more abused a term in the history of philosophy than “representation,” and my use of this term differs both from its use in traditional philosophy and from its use in contemporary cognitive psychology and artificial intelligence.... The sense of “representation” in question is meant to be entirely exhausted by the analogy with speech acts: the sense of “represent” in which a belief represents its conditions of satisfaction is the same sense in which a statement represents its conditions of satisfaction. To say that a belief is a representation is simply to say that it has a propositional content and a psychological mode.

John Searle (1983) Intentionality: An Essay in the Philosophy of Mind. p. 12

We define a semantic network as "the collection of all the relationships that concepts have to other concepts, to percepts, to procedures, and to motor mechanisms" of the knowledge".

In joint scientific efforts extending over twenty years, initially in collaboration with J. C. Shaw at the RAND Corporation, and subsequently with numerous faculty and student colleagues at Carnegie-Mellon University, they have made basic contributions to artificial intelligence, the psychology of human cognition, and list processing.